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Introduction

  • Once you’ve downloaded all the requisite source information her the package’s instructions, you can build the package and re-create Figures and Tables published in Roy2025
  • This vignette is provided to enable anyone to see the source data and methodology behind our publication.

Figure 1

1A - Continental US A11

1B - A11:01 by County

1C - NDMP Correlations

NMDP Values are not publicly available for privacy reasons. Please contact co-Author Martin Maiers for inquiries.

1D - A11:01 by CA County

1E - A11:01 by CA by H4 Hexagon

1F - A11:01 Catchment

  • For a table of A11:01 catchment, refer to Table 2 below.

Figure 2

2A - B58:01 by County

2B - B58:01 in MS by County

2C - B58:01 in MS by Hexagon

2D - B58:01 Catchment

Tables

Table 1: United States 2020 Census Adjusted HLA-A*11:01 Genotypic Frequencies

## Joining with `by = join_by(nmdp_race_code)`

Table 2: HLA-A*11:01 Population-adjusted genotypic frequencies for top 11 NCI Catchment areas.

## Warning in instance$preRenderHook(instance): It seems your data is too big for
## client-side DataTables. You may consider server-side processing:
## https://rstudio.github.io/DT/server.html

Supplemental Tables

Supplemental Table 1 - California County population-adjusted HLA-A*11:01 Genotypic frequencies

Supplemental Table 2 - United States 2020 Census Adjusted HLA-B*58:01 Genotypic Frequencies for Mississippi

## Joining with `by = join_by(nmdp_race_code)`

Supplemental Table 3 - Mississippi County population-adjusted HLA-B*58:01 Genotypic frequencies

Supplemental Table 4 - HLA-B*58:01 Population-adjusted genotypic frequencies by NCI Catchment areas. {#st4}

## Warning in instance$preRenderHook(instance): It seems your data is too big for
## client-side DataTables. You may consider server-side processing:
## https://rstudio.github.io/DT/server.html

References